Classify recipe text to cuisine using NLP and Logistic Regre
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Discover the fascinating world of NLP and logistic regression in this beginner-friendly project. Learn how to predict the country of origin of recipes using ingredients and create a document term matrix. Gain valuable insights into the workings of logistic regression and NLP concepts, equipping you for future machine learning projects in the NLP field.
At a Glance
Have you ever wondered why certain foods taste the way they do? Well, in this project, we will use NLP (Natural Language Processing) to determine the country of origin of recipes using the ingredients. This project will introduce you to NLP and the logistic regression algorithm. NLP is a fantastic field with many applications, but we’ll focus on a straightforward beginner project in this guided project. Here we will create a document term matrix (aka term-frequency matrix) using our recipes ingredients and plugging it into a logistic regression model to predict the county of origin.
This guided project will give you a high level introduction into how exactly logistic regression works using a simple example. We will also introduce simple NLP concepts in this guided project, giving you exposure and an opportunity to learn about how you can represent a document as a vector of terms (words). Using these tools, you’ll be equipped to tackle many other machine learning projects and dive deeper into the NLP field and supervised classification.
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